Methodology of Consciousness Theory

Consciousness research suffers from a methodological and categorical double deficit. While the natural sciences explicitly discuss and justify their methods, consciousness research lacks systematic methodological reflection. This methodological deficit is functionally related to a basic categorical error: the confusion of epistemic levels of description with ontological entities. This level confusion results in three pseudo-problems, which are treated as central research questions, namely the body-soul problem, the hard problem and the what-is-it-like problem.

The present article develops a reconstructionist method as a solution to this double deficit. This method avoids the categorical confusion between levels of description and ontology and identifies functional necessities instead of arbitrary correlations. Central is the insight that consciousness does not emerge from dead matter, but from autocatalytic organization. The model of causal collapse describes consciousness as a state of maximally non-factorizable causal entanglement in neuronal systems that arises when a measure of causal separability Σ(t) falls below a critical threshold Σc.

The thesis systematically reconstructs the necessary conditions for consciousness: autocatalytic organization as a biological foundation, the causal nucleus as an evolutionary structural principle from the cell nucleus to the default mode network, electrical signal transduction in the nervous system, and finally causal collapse as a mechanism of phenomenal experience. Phylogenetic development shows how the causal nucleus as a structural principle permeates evolution from prokaryotes to early nervous systems to human consciousness.

Different forms of consciousness are derived from specific collapse structures: primary consciousness as sensorimotor collapse, self-consciousness as recursive collapse with self-model, intentionality as prospective collapse, and affective consciousness as limbically integrated collapse. The theoretical positioning shows that the model integrates and specifies Integrated Information Theory, Global Workspace Theory and plasticity approaches.

Empirically, the model is supported by the Perturbational Complexity Index (PCI), functional connectivity patterns, and characteristic differences between states of consciousness. For predictions that are not directly proven, concrete test procedures are proposed. The method transforms arbitrary correlations into functional necessities and opens up new avenues for empirical research, artificial systems of consciousness and clinical applications.